ANS. COLUMN I COLUMN II 1 outcome A In the long run, the empirical approaches the actual probability 2 Conditional probability B A SUBSET OF THE SAMPLE SPACE 3 Sample space C the result of a single trial in a probability experiment 4 No gain or loss D Addition rule, add the individual probabilities of each event and subtract the probability that they both occur. 5 And probability E Expected value is to break even 6 The law of large number F the probability of an event occurring, given that another event has already occurred 7 Independent events G all possible outcomes of a probability experiment 8 event H when the occurrence of one of two events does not affect the probability of the occurrence of the other event. 9 Fundamental counting principle I Multiplication rule, two events happening in sequence 10 Or probability J The numbers of way two or more events can occur
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
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ANS. |
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COLUMN I |
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COLUMN II |
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1 |
outcome |
A |
In the long run, the empirical approaches the actual |
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2 |
Conditional probability |
B |
A SUBSET OF THE |
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3 |
Sample space |
C |
the result of a single trial in a probability experiment |
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4 |
No gain or loss |
D |
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5 |
And probability |
E |
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6 |
The law of large number |
F |
the probability of an event occurring, given that another event has already occurred |
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7 |
Independent events |
G |
all possible outcomes of a probability experiment |
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8 |
event |
H |
when the occurrence of one of two events does not affect the probability of the occurrence of the other event. |
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9 |
Fundamental counting principle |
I |
Multiplication rule, two events happening in sequence |
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10 |
Or probability |
J |
The numbers of way two or more events can occur |
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